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Enregistrement W2340469576 · doi:10.1055/s-0036-1583260

The Impact Factor and Scientific Journals

2016· article· en· W2340469576 sur OpenAlexaboutno aff
Jeffrey C. Wang

Notice bibliographique

RevueGlobal Spine Journal · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueGlobal Health and Surgery
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésImpact factorAudience measurementScrutinyPopularityMedicineEditorial boardCitationMandateNoticeQuality (philosophy)Library sciencePolitical scienceLawComputer science

Résumé

récupéré en direct d'OpenAlex

Thanks to you, our readership, our combined Global Spine Journal/Evidence-Based Spine-Care Journal has enjoyed substantial popularity in terms of submissions. In response to this demand, the AOSpine International Board has given us permission to increase our number of annual issues from 6 to 8. This increase in annual issues has come with a number of stipulations, of which one of the leading ones is the mandate to achieve a competitive Impact Factor (IF) over the next 2 years. As a relatively young PubMed listed publication we needed to accumulate at least 2 years of continuous quality publications to qualify for this rating. Thanks to your many submissions and our outstanding volunteer reviewers we now have reached a point where we are able to stand the scrutiny of the scientific community at large. We thought that you might be interested in learning more about the ways the IF is determined. The IF is a proprietary calculation provided as a paid service by Thomson Scientific, a subsidiary of the Thomson Reuters Corporation based in New York, USA and Toronto, Canada. Basically, the IF is calculated as the quotient of the number of citations that the journal in question received in the over 11,000 indexed journals in the year after a 2-year review period. This number of citations is then divided by the number of “citable items” published in that journal in the 2 reviewed years. In example, for GSJ/EBSJ the number of citations that our articles published in 2014 and 2015 receive in other indexed journals in 2016 is divided by the number of “citable articles” that we published during the 2014–2015 period. This number is then published as the “2016 IF” in 2017. As in anything metric, the IF can and will then be used for comparison to other specialty journals that are indexed in the Web of Science (IS), which is a Thomson Reuters subscription-based service consisting of about 11,000 scientific publications. GSJ/EBSJ has now acquired enough of a track record to go up for a rating of an IF and as stated our Board and our peers will scrutinize our rankings closely as a measure of our success. There are several well-established strategies to improve an IF calculation. The main recipe is to limit the amount of “citable” items to such articles that stand a chance to be quoted elsewhere. This puts biographies, abstracts, and especially case reports into the category of “undesirable” publications, as they are usually viewed as “citable” articles by Thomson Scientific, but unfortunately have a very low likelihood of actually getting quoted in other scientific publications. For us in AOSpine and our Editorial Board the decision not to accept case reports (CR) was a difficult one. We are aware that we serve a global interdisciplinary constituency of spine surgeons. For many colleagues, formal research resources have been hard to come by—a CR of an interesting appearing or unusual case together with a literature review is a welcome stepping stone into the world of published academia. Similar motivations have made CRs the preferred entry point into the world of peer-reviewed scientific publications for trainees around the world. Sadly in a world of increasing push for fiscal efficiencies the work load required to process CRs stands in no relation to the number of submissions and the chances that such a CR will become a quotations hit. In our world of “Evidence-Based Medicine” CRs do not even register as they form the very bottom of the pyramid at Level 5! In looking at these negatives, are there any justifications left to keep looking at CRs or will they become extinct in the not too distant future? Interestingly, CRs have held a significant place in medicine as an early warning system for unusual or perplexing developments and observations. Two classic examples for CRs being the harbingers of much bigger things to come can be found in the world of infectious diseases with HIV and Ebola having been first reported on a case basis well before any mainstream scientific investigations were started.1 2 In spine traumatology it was the landmark CR by Frank Eismont that raised our awareness about cervical dislocations with traumatic disk herniations possibly leading to secondary neurologic damage in case of an inopportune reduction.3 Another important aspect of CRs presents with very rare complications or events—such as perioperative blindness.4 So CRs can have a vital role as an early warning alarm prior to any formal investigation. In our era of information overflow the occasion where such meaningful nuggets can achieve recognition has sadly dropped to near nil. As Editors-in-Chief of GSJ/EBSJ we hope that our decision to concentrate on your high-quality scientific contributions and achieve a respectable IF rating will find your full support. And all other things aside—should you be convinced that you stumbled upon a major breakthrough insight from a case report, please let us know!

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,048
score de la tête « metaresearch » (Gemma)0,325
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Bibliométrie
Catégories consensuellesaucune
DomaineSignal candidat: Évaluation · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,955
Score d'incertitude au seuil0,252

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0480,325
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0060,002
Bibliométrie0,0450,085
Études des sciences et des technologies0,0050,019
Communication savante0,0580,034
Science ouverte0,0040,010
Intégrité de la recherche0,0090,012
Charge utile insuffisante (le modèle a refusé de juger)0,0510,045

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,037
Tête enseignante GPT0,383
Écart entre enseignants0,346 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeThéorique ou conceptuel
DomaineÉvaluation
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2016
Routes d'admission1
Résumé présentoui

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